In the first post World War II identity theories (e.g., Place 1956, Smart 1962), mind brain identities were held to be contingent. However, in work beginning in the late 1960's, Saul Kripke (1971, 1980) convinced the philosophical community that true identity statements involving names and natural kind terms are necessarily true and furthermore, that many such necessary identities can only be known a posteriori. Kripke also offered an explanation of the a posteriori nature of ordinary theoretical identities such as that (...) water = H2O. We identify the kinds and substances involved in theoretical identities by certain of their contingent properties. What we discover when we discover a theoretical identity is the underlying nature of the kind that we identify by those contingent properties. Now, of course, it was being a posteriori, not being contingent, that mattered to the identity theorists anyway, so the necessity of identity is not, in itself, damaging to mind brain identity theories. However, Kripke also argued persuasively that the alleged mind brain identities could not be treated in the same way as ordinary theoretical identities. We "identify" pain by feeling it, and surely how it feels is an essential property of pain, not a contingent property. Thus, a mind body identity theory must provide a different explanation of why its identities are a posteriori. A new wave of materialists has appeared on the scene with a new strategy for explaining [1] the a posteriori nature of its alleged identities. The strategy is to locate the explanation for the a posteriori nature of mind body identities, not on the side of the world, but on the side of the mind -in different ways of thinking about or imagining, or in different concepts. Thus, on this new view, there is only one property—this brain process type, which is identical with this pain.. (shrink)
David Marr provided a useful framework for theorizing about cognition within classical, AI-style cognitive science, in terms of three levels of description: the levels of (i) cognitive function, (ii) algorithm and (iii) physical implementation. We generalize this framework: (i) cognitive state transitions, (ii) mathematical/functional design and (iii) physical implementation or realization. Specifying the middle, design level to be the theory of dynamical systems yields a nonclassical, alternative framework that suits (but is not committed to) connectionism. We consider how a brain's (...) (or a network's) being a dynamical system might be the key both to its realizing various essential features of cognition — productivity, systematicity, structure-sensitive processing, syntax — and also to a non-classical solution of (frame-type) problems plaguing classical cognitive science. (shrink)
Human cognition is rich, varied, and complex. In this Chapter we argue that because of the richness of human cognition (and human mental life generally), there must be a syntax of cognitive states, but because of this very richness, cognitive processes cannot be describable by exceptionless rules. The argument for syntax, in Section 1, has to do with being able to get around in any number of possible environments in a complex world. Since nature did not know where in the (...) world humans would find themselves—nor within pretty broad limits what the world would be like —nature had to provide them with a means of “representing” a great deal of information about any of indefinitely many locations. We see no way that this could be done except by way of syntax— that is, by a systematic way of producing new, appropriate representations as needed. We discuss what being systematic must amount to, and what, in consequence, syntax should mean. We hold that syntax does not require a part/whole relationship. The argument for the claim that human cognitive processes cannot be described by exceptionless rules, in Section 2, appeals to the fact that there is no limit to the factors one might.. (shrink)
Any successful account of general terms must explain our ability to apply terms correctly to new instances. Many philosophers have thought resemblance offers an ontologically sparse basis for such an account. However, Any natural and plausible account of general terms on the basis of resemblance requires quite a rich ontology, Including at least second order properties and relations. Given a sufficiently rich structure of resemblances, We can surely account for the application of many general terms. I argue, However, That our (...) ability to recognize shapes and to apply terms for shapes cannot be explained on the basis of resemblance. (shrink)
David Marr provided an influential account of levels of description in classical cognitive science. In this paper we contrast Marr'ent with some alternatives that are suggested by the recent emergence of connectionism. Marr's account is interesting and important both because of the levels of description it distinguishes, and because of the way his presentation reflects some of the most basic, foundational, assumptions of classical AI-style cognitive science . Thus, by focusing on levels of description, one can sharpen foundational differences between (...) classicism and potential non-classical conceptions of mentality that might emerge under the rubric of connectionism. (shrink)
Abstract Andy Clark argues that the reality and causal efficacy of the folk psychological attitudes do not require in?the?head correlates of the that?clauses by which they are attributed. The facts for which Fodor invokes a language of thought as empirical explanation?systemati?city, for example?are, Clark argues, an a priori conceptual demand upon propositional attitude ascription, and hence not in need of empirical explanation. However, no such strategy can work. A priori demands imposed by our practices do not eliminate the need for (...) empirical explanation of how these demands are satisfied by particular beings. And given the vast number of potential beliefs, and the interrelationships they exhibit, no one has the slightest idea how they might be explained except by in?the?head syntax. (shrink)
